Nutrition Landscape Information System (NLiS)
Does it at least consistently classify consumers into strong and weak consumers? The study found that health literacy increases with education and people living below the level of poverty have lower health literacy than those above it. Post-vaccination testing also identifies uninfected infants who did not respond to vaccination and require re-vaccination because of ongoing exposure to infected household contacts including their mothers. Around BC, Anaxagoras stated that food is absorbed by the human body and, therefore, contains "homeomerics" generative components , suggesting the existence of nutrients. Breastfeeding practices worldwide are not yet optimal, in both developing and developed countries, especially for exclusive breastfeeding under 6 months of age. There are two subcategories: Relationship between smoking and dental status in , , , and year-old individuals.
B. Nutritional assessment
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If the programme consists of scaling up an intervention that has proved effective elsewhere, at experimental level, the causal interpretation is simplified. If it is based on strong, but as yet unverified, hypotheses, it is more difficult to automatically attribute the observed effects to the intervention .
Insofar, however, as indicators of different confounding factors likely to influence the situation were recorded before and after the implementation of the programme, statistical adjustments may be used during the analysis to improve interpretation - hence the importance of collecting these additional indicators.
A with-without comparison can then be made between two areas, one benefiting from the programme and the other not external control group. This poses the problem of initial comparability of the two areas: Alternatively, two areas may be compared with an unequal level of implementation of the programme internal control group or, more simply still, groups of individuals or households may be compared which have not benefited of the programme at the same level, since the level to which target individuals are reached by programmes is generally variable.
Ideally, the impact evaluation should follow an experimental design, with randomization of the individuals or areas to receive or not the intervention. This is the most rigorous way to proceed in order to be able to conclude on the actual impact of the intervention. In most cases, an impact evaluation of the crude effect will be quite acceptable, i. Elements suggesting a cause and effect relationship can be formulated, but without seeking absolute proof, if plausibility of the effectiveness of the programme appears sufficient to those in charge.
In , Vietnam implemented a national strategy of supplementation with vitamin A capsules through health centres to combat xerophthalmia. Three years later, an evaluation recorded a very high coverage of the populations at risk by the programme and, in addition, did not observe any clinical case of xerophthalmia based on a nationally representative sample of pre-school children.
In this case, there is little doubt that the result is directly linked to the programme, even if the evaluation cannot formally prove it: Plausibility of the link is very strong here. On the other hand, during the same period another country launched a programme to improve household food security, encompassing a certain number of measures such as the support to farm-gate prices for food crops and a reorganization of local markets on the basis of previously identified weaknesses.
The evaluation of the programme after several years of operation showed a slight improvement in the situation. Without a rigorous evaluation design, it is impossible to evaluate the relative share of improvement due to the programme or to other factors. These elements will be useful each time it has to be decided whether the programme should be continued or not. A group of convergent elements based on the available indicators will be established in order to reach a conclusion on its likely effectiveness.
Often, for financial reasons, a programme cannot be implemented straight away in all the targeted areas; these will be incorporated into the programme gradually. However, the necessary indicators can usefully be collected in all the zones from the start, for this will provide elements for comparisons between zones with and without the programme and before and after the programme, which will in turn be useful to document the plausibility of effectiveness of the intervention.
This will make it easier to evaluate the sustainability of the programme by measuring the effect simultaneously in areas where the programme has been in operation for increasing durations. The purpose of an evaluation is not only to measure impact, but also to allow the programme to be adapted to changing conditions.
An early warning system will be evaluated primarily on its ability to foresee any worsening in the consequences of food crises among the groups most at risk; it will thus comprise a number of indicators on the strategies implemented according to the degree of vulnerability, on the levels of food consumption and on the nutritional status of these groups, for example.
However, it will also involve indicators to assess whether the situation is evolving towards greater stability improvement of climatic conditions or of food production, for example so that the primary objective of the programme can be refocused if the initial goal has become obsolete. When evaluating programmes, a distinction is made in practice between impact which is the direct result of the programme, and longer term benefits, which encompass the indirect effects of the programme on the target population, or indeed the whole population, in terms of health, economic and social situation.
In the case of an isolated programme, attention may be focused on its specific impact, but in the context of overall monitoring of a policy or group of programmes, the impact of the complete set of strategies will be the subject of regular evaluation - which will aim not so much at providing evidence of the effectiveness of one or another programme, but rather at verifying whether the situation is evolving in the desired direction, taking into account external circumstances and the programmes in operation.
Apart from regular measurement of progress, this will also provide an opportunity to check that the conceptual analysis on which the choice of different strategies was based is still relevant, or to see whether activities need refocusing.
The aim is to examine changes in the situation in terms of the general objectives of the policy adopted, implying regular collection of a certain number of indicators of risk and of causes, as well as major basic indicators, to be used by country planners and by international agencies or donors, and assessment of trends.
This corresponds to one of the nine strategies proposed in by the ICN Plan of Action - which has been taken up since then by a number of countries for their national action plan - that of "assessing, analysing and monitoring nutrition situations". This implies setting up a proper nutrition surveillance system applied to planning.
These national plans have explicit general goals with an order of magnitude for expected reductions in malnutrition levels or improvements in various sectors. As a result of its plan, Ecuador, like other countries, anticipates fulfilling the following objectives in terms of improvements in the nutritional status of the population: Objectives will be all the more explicit and realistic if there is a recent "baseline" and an idea of trends in the past or in neighbouring countries or in countries with similar constraints.
However, waiting for a complete baseline to be available would not be reasonable; one can start with existing data from the various services, or with rapid surveys carried out on a one-off basis when there are no data for a specific problem deemed to be important.
Yet implementing a policy must be an opportunity for also setting up a monitoring system - covering at least the main indicators of status and causes of malnutrition, which will be put in perspective with major agro-ecological and socio-economic indicators - in order to have an ongoing "log-book" of the situation and of time trends.
After analysis, a country considers that the prevalence of low birthweight is too high and that the goal of reducing it implies i strengthening the performance of pre-natal health care services, ii promoting a better diet for mothers-to-be, either through better use of local food or the specific distribution of food supplements, and iii encouraging a reduction in the workload of pregnant women through various measures.
The precise actions to be undertaken and any precise quantification in terms of intermediate objectives depend of course on the specific country situation. Monitoring implementation of these actions will be based on a quantitative and qualitative assessment of the performance level of the units concerned number of rations distributed or number of persons who have used the services, percentage of services which have given advice and care of adequate quality to pregnant women, quality of rations distributed, level of use of the advice and care by the beneficiaries, etc.
At programme evaluation, outcomes and impact indicators can be based on changes in the frequency of consumption of certain foods by the women attending the units, or on changes in average birth weight and prevalence of low birth weight in the target population. Indicators do not all have the same value.
In theory this depends on their ability to best reflect a sometimes complex reality, but a trade-off will have to be found given the level of difficulty in collecting them. Therefore, indicators are traditionally defined according to a certain number of properties that allow their value to be assessed, at least in a given context. Obviously they do not all present all the characteristics of a good indicator, so that it will have to be decided which characteristics are to be given priority when selecting indicators.
It entails that the indicator does indeed offer a true and as direct as possible measurement of the phenomenon considered. At conceptual level, it depends first of all on how clearly the phenomenon to be measured has been defined and also on the ability to measure it directly. This poses a problem where the phenomenon to be measured is linked to a multidimensional concept, and is thus difficult to measure in a global way. There must, in particular, be a consensus on the level and significance of cut-off points for classification.
A major standardization effort has for example been made in the field of measuring nutritional status and recommended dietary intakes, and this has helped give a more precise framework for use of the corresponding indicators.
This is not always the case in other sectors, either because the indicators lend themselves less to quantification, or because such quantification depends very much on local circumstances. Relevance in the context of planned use must, in this case, be based on a local analysis shared among the different stakeholders, as we will see below.
Moreover, even if the indicator correctly describes a phenomenon, any systematic bias in collecting the corresponding information due to measurement methods or instruments will affect its validity. There is no overall indicator to provide a picture of "nutritional status", therefore a decision has to be made on which specific aspect of nutritional status is to be characterized: Even in the case of energy status, for example, no overall indicator is available; the indicator which is the most relevant for the aspect one wishes to prioritise - physical, biochemical, functional, etc.
For assessing the nutritional situation of a population, a set of individual anthropometric measurements have been adopted, that, when compared to reference values, make it possible to assess the status of individuals or populations; they constitute the corpus of relevant indicators to be used preferably over any other. However, when using these indicators, one should be aware of limitations to their validity: In the field of "food security", - again a very broad concept difficult to translate in simple terms - there is a considerable number of indicators, each reflecting a specific aspect and thus only relevant for a given aspect.
For example, in order to describe the level of food insecurity of a household, an indicator based on a quantitative criterion of food consumption or a qualitative criterion of the perception by the household of its own food insecurity situation will be more relevant than an indicator of prices of foodstuffs on the local market.
Imprecision due to measurement methods, variability from one day to another may limit the reproducibility of the indicator. This causes an increase in variance and implies that larger samples will be needed in order to assess correctly the level of the indicator and its variations over time. Subjectivity bias is a frequent risk with indicators deriving from qualitative surveys, as they describe behaviours or opinions of households, for example, since the personality or technique of the person conducting the survey may influence the nature of responses.
Moreover, respondents to a questionnaire or subjects under observation can modify their responses or behaviour in a normative way. People who are overweight, for example, often minimise their actual food intake when interviewed for a food consumption survey.
Reproducibility guarantees that an indicator can be measured at repeated intervals in a comparable manner - a quality which is crucial when using the indicator to assess and monitor the situation. A complementary characteristic is specificity, which refers to the ability to identify those not affected by the risk or characteristic.
Sensitivity is measured in practice by the ratio of the number of individuals identified by the indicator as being at risk or as having the characteristic to the number of individuals who are actually at risk or have the characteristic. Specificity is the ratio of the number of individuals not identified by the indicator to the number of individuals who are actually not at risk or do not possess the characteristic.
Sensitivity thus gives an idea of the degree of correct or misclassification linked to the use of an indicator. Not all indicators lend themselves to an assessment of sensitivity. Sensitivity applies essentially to indicators with cut-off values. Moreover, sensitivity is measured with respect to a given goal; sensitivity of an indicator such as weight-for-height at a given cut-off value will not be the same, depending on whether the goal is to identify children who are wasted or those who are at risk of dying in coming months.
Data for quick computation of these parameters sensitivity, specificity are not always available, so in practice, reference is made to existing data from the literature to find those closest to the chosen cut-off values and expected prevalences. One particular aspect of sensitivity is the ability of an indicator to measure change, not in order to identify or target a particular category of individuals as previously but to detect the smallest possible change in the phenomenon described, in a significant way.
While sensitivity, in general, is important when establishing a baseline, and for defining the target groups to which the activities will be directed, this ability for measuring change is crucial for assessing or monitoring trends, in particular to detect changes in the situation during implementation of the programme. However, it is relatively inert when assessing small progressive changes in nutritional status over time, and the weight-for-height indicator will be preferred in this case, since it is more sensitive to change.
Also, urinary iodine will respond to introduction of salt iodization in a region quicker than prevalence of goitre, which will decline only slowly. In addition to these inherent characteristics of indicators, their operational value should be examined; it will be essential when the choice of indicators is made, especially in terms of speed and cost of collecting data for producing these indicators.
It represents the practical possibility of making available the indicator in question. It implies the feasibility of collecting the corresponding data by whatever means. There are indicators described as "ideal" which nobody is in practice able to collect.
As a result of major international conferences and of programmes that have followed them during the last two decades, many of the required indicators are already systematically and regularly collected within the framework of such programmes and are thus very easily available. It affects use of the indicator not only at the descriptive stage, but also when monitoring the situation.
An indication of the quality of the measurements, of sampling and of the confidence interval of the result is essential here to assess dependability. Occasionally, it has been observed that the number of malnourished children estimated by nutritional surveys carried out by various organizations on identical populations and during the same periods, differed substantially; using the results for targeting purposes or for monitoring the situation is ruled out in this case.
The reason was usually the lack of precision of the anthropometric measurements or of the definition of age, and occasionally a sampling problem. Data on food consumption obtained by weighing food are more precise than those obtained with the "recall" technique, although the former implies technical constraints and can therefore only apply to small samples, so that there is a broad confidence interval in the results.
Recall techniques, on the contrary, can easily be applied to a large sample, obviously with a smaller confidence interval. The various available data must therefore be carefully examined before using them for monitoring purposes, and a choice will sometimes be made between data collected with a higher level of accuracy but lower power at the level of the target population, or the opposite.
On this depends, in part, the speed and frequency with which the indicator can be regularly measured. When the data necessary for the construction of the indicator need to be collected specifically for evaluation or monitoring, cost should be considered; it depends on the difficulty and sophistication of the measurements, the accessibility of the objects or people to be measured, the frequency of collection and the complexity of the analysis subsequently.
The cost of non-collection may be measured, in the case of a food subsidy programme, for example, by the difference between the cost of the programme if it is carried out without particular targeting, in the absence of any indicator allowing targeting, and the cost of the programme for the target population, plus the cost of targeting, if the programme is to be directed at a high risk group only. Nevertheless, information on the cost of collecting an indicator for each situation is seldom available.
It is difficult to measure, and estimates are generally based on the cost of different types of survey within the country, taking account of the fact that several indicators are collected at the same time. Indicators can be categorized schematically in the following way according to the level at which they are produced or made available:.
They include both indicators regarding the implementation of services as well as indicators regarding the situation or the impact of actions under way. It is generally easy to obtain them from the departments concerned, which usually have time series that are very useful in distinguishing medium- and long-term trends.
Even so, it is not always possible to cross-tabulate these indicators, since they do not necessarily come from the same databases and are accessible only in a relatively aggregated form. It is also difficult to verify the quality of the original data.
Lastly, even if the data are collected on a frequent basis monthly reports, for example , recovery and analysis may take too long. Such data tend not to be immediately accessible except in summary form, although it is easy to organize new analyses with the departments in charge of them. These data allow statistical cross-tabulation to be made between the many variables collected simultaneously on the sample. Although carried out at best at very long intervals, they can be updated with reasonable projections, especially if information on trends in the fields of interest, based on routinely collected data, are also available.
These data are often kept together in national statistical offices. They consist of a regular collection of information based on a small number of selected indicators. The system varies by country, those that perform best are based on an explicit conceptual framework and are linked to a clear decision-making mechanism.
They can represent a sound basis for central monitoring. A particular category is derived from surveys conducted by international bodies for various purposes: These cross-sectional surveys are conducted directly at household level on samples which are representative at national level but of variable size; they include a wide variety of indicators in number, goals and qualities and are now frequently repeated.
Although conducted peripherally, they are generally available and used centrally. These sources, which are in principle fairly reliable, benefit from an advanced level of analysis allowing causal inference to be derived of relationships among various household indicators, and with individual indicators, such as nutritional status. They represent a precious source when establishing a baseline and when analysing causes prior to launching an intervention. These are constructed primarily on the basis of routinely collected data from local government offices, community-based authorities.
They are usually passed on as indicators or raw data to the central level, and then sent back to the decentralized levels, with varying degree of regularity, after analysis. They are often disaggregated by district or locality, but are not always representative, since they often refer only to users of the services under consideration. They are generally grouped together at the central administrations of regions or administrative centres.
The indicators relate primarily to activities that lend themselves to regular observation, either because they record activities indicators of operation or delivery of services or because they are necessary for decision-making crop forecasts, unemployment rates or for monitoring purposes market prices of staples, number of cases of diseases, etc.
They do not necessarily include indicators of the causes of the phenomena recorded and are not in principle qualitative indicators. Indicators collected at decentralized levels should meet both the needs of users on these levels and also those of users on the central level for the implementation and monitoring of programmes. If these regularly compiled indicators do not have any real use at the local level and are intended only for the national central level, there is a danger that their quality will drop over time, for lack of sufficient motivation of those responsible for collection and transmission - and gaps are therefore often found in available data sets.
Nevertheless, they are invaluable in giving a clear picture of the situation on the regional or district level, together with medium-term trends. Generally speaking, their limitation is the low level of integration of data from different sectors. A certain number of indicators, particularly those concerning the life of communities or households and not touching on the activities of the various government departments, are not routinely collected by such departments and are in any case not handed on to the regional or central offices.
They are sometimes collected at irregular intervals by local authorities, but most often by non-governmental organizations for specific purposes connected with their spheres of activity - health, hygiene, welfare, agricultural extension, etc.
Analytical capabilities are often lacking at this level, and the available raw data may not have led to the production of useful indicators. Action therefore should be taken to enhance analytical capacities or else sample surveys will have to be carried out periodically on these data in order to produce indicators. A sound knowledge of local records and their quality is needed to avoid wasting time.
New collection procedures often have to be introduced for use by local units, while being careful not to overload them or divert them from their own work. Otherwise a specific collection has to be carried out by surveying village communities targeted for analysis or intervention.
These surveys are vital for a knowledge of the situation and behaviours of individuals and households and an evaluation of their relationship with the policies introduced. In general, they offer an integrated view of the issues concerned. They may have the aim of supplying elements concerning the local situation and local analysis, in order to confirm the consensus of the population and of those in charge as to the situation and interventions to be carried out, and also to allow an evaluation of the impact of such interventions.
The participatory aspect should be emphasized rather than the precision or sophistication of data. An FAO work on participatory projects illustrates issues of evaluation, and especially the choice of indicators in the context of such projects FAO If data already collected are used or if a new survey is carried out for use on a higher level, the size and representativeness of the sample must be checked, and it must be ensured that the data can be linked to a more general set on the basis of common indicators collected under the same conditions method, period, etc.
Verification of the quality of the data is crucial. Before undertaking a specific data collection, a list of indicators and of corresponding raw data should be developed which can be used by services at all levels; it is not unusual to find that surveys could have been avoided by a better knowledge of the data available from different sources.
To track down these useful sources and judge the quality of the data available and their level of aggregation, a good understanding is needed of the goals and procedures of the underlying information system. The country had set up a monthly national information system on production estimates for 35 crops, covering information on crop intentions, areas actually planted, crop yields and quantities harvested in each state.
The information was obtained during monthly meetings of experts at various levels - local, regional and national. The information was then put together at the state level, and then at the national level, reviewed by a national committee of experts, and sent on to the central statistics office. The different levels thus had some rich information at their disposal, coming from a range of local-level sources.
Although it was certainly fairly reliable, being confirmed by a large number of stakeholders and experts, its precision could not be defined, in view of its diversity. The usefulness of such data varies depending on information needs and thus on the quality of the data required. Data concentrated at the central level are probably useful primarily for analysing trends. On the other hand, apart from the figures, more general information on production systems exists at local level, and this can be useful for identifying relevant indicators of causes, or for simplifying monitoring of the situation.
We have seen that there is a great number of indicators which differ widely in quality; the availability of corresponding data is variable, and any active collection will be subject to constraints.
Therefore the choice of indicators must be restricted to the real needs of decision makers or programme planners. This implies that a method is needed for guiding the choice. The main elements that will guide choice are: Any intervention is based on an analysis of the situation, an understanding of the factors that determine this situation, and the formulation of hypotheses regarding programmes able to improve the situation.
A general framework was presented earlier see Figure , representing a holistic model of causes of malnutrition and mortality, which was endorsed by most international organizations and nutrition planners.
However, the convenient classification that it implies, for instance into levels of immediate, underlying or basic causes needs to be operationalized through further elaboration in context. The benefit of constructing such a framework, over and above the complete review of the chain of events which determine the nutritional situation, is to allow the expression, in measurable terms, of general concepts which, because of their complexity, are not always well defined.
For example, it is not enough to refer to "food security"; one should state which of the existing definitions is to be used, on which dimensions of food security the focus is placed and the corresponding indicators. The use of conceptual frameworks when implementing programmes or planning food and nutrition is not new. Many examples have been developed, focusing on different aspects.
The concept of food security is generally perceived as that of sufficient availability of food for all. However, several dozen different definitions have been proposed over these last 15 years!
This concept may, for example, comprise different aspects depending on the level being related to: In the first case, analysis will focus on agricultural production, and in the second the emphasis will be on improving the resources of those who lack access to a correct diet. This preliminary brainstorming exercise will allow a better definition of the perceived chain of causes production shortfall, excessive market prices, defective marketing infrastructures, low minimum wage, low level of education, etc.
It will then be easier to consider potential indicators of the situation and its causes, or potential indicators of programme impact. Obviously it is not so much the final diagram which is of importance as the process through which it was developed.
Insofar as the relations between all the links of the chain of events or flow data, depending on the type of representation have been discussed step by step and argued with supporting facts, the framework will be adapted to the local situation and will become operational. Methodologies have been developed for making this process effective in the context of planning, for example with the method of "planning by objectives" see ZOPP , which comprises several phases: During this planning process, all programme activities, corresponding partners, necessary inputs and resulting outputs as well as indicators for both monitoring implementation and evaluating impact of the programme will be successively identified.
The method acts as a guide for team work, encouraging intersectoral analysis and offering a simplified picture of the situation, so that the results of discussions are clear to all in the team.
Let us again take the example of a problem of food security. It can be broken down into three determining sectors: A series of structural elements can be defined for each sector: These elements affect both production levels and operation of markets. A certain number of macro-economic or specific policies will affect one or all the elements in this block. Each block can be considered in a similar way, and this will provide the groundwork for a theoretical model of how the system works see C.
The final steps in order to operationalize the model are i that of defining indicators that will, in the specific context of the country, reflect the key elements of the system, and ii , once policies and programmes have been chosen, that of identifying which of these indicators are useful for monitoring trends and evaluating programme impact.
This will be the basis for an information system reflecting the overall framework of the programme and how it should work. Another method has been proposed by researchers from the Institute of Tropical Medicine in Antwerp based on their field experience in collaboration with different partners Lefèvre et al.
Basically, it stresses the participatory aspect, with the aim of obtaining a true consensus on the local situation, the rationality of interventions in view of the situation, and the choice of indicators. It includes first a phase in which a causal framework is developed with the aim of providing an understanding of the mechanisms leading to undernutrition in the context under consideration. The framework is constructed in the form of a schematic, hierarchized diagram of causal hypotheses formulated after discussions among all stakeholders.